名古屋大学 · 医学
Kidokoro教授の研究室では、未熟児の脳発達と脳障害の画像診断・予後予測に注力しています。特に、出生時から胎齢補正年齢に達した時点までの脳の構造的変化をMRIやaEEGを用いて精密に評価し、早期の神経発達障害の予測や介入の可能性を追求しています。脳の白質・灰色質の成長異常や、機械的換気・静脈栄養などの周産期要因との関連についても、客観的な画像スコアリングシステムの構築を目指しています。
Figures are computed from collected data and may differ slightly.
Very preterm infants demonstrate a high prevalence of injury and growth impairment in both the WM and gray matter. This MR imaging scoring system provides a more comprehensive and objective classification of the nature and extent of abnormalities than existing measures.
At term-equivalent age, VPT infants showed both brain injury and impaired brain growth on MRI. Severe brain injury and impaired brain growth patterns were independently associated with perinatal risk factors and delayed cognitive development.
Patterns of brain injury differed between cohorts. Prolonged mechanical ventilation and parenteral nutrition were identified as independent perinatal risk factors. The prognostic value of the TEA-MRI score was rather limited in this well-performing cohort.
Although DEHSI may represent disturbances in white matter structure, as illustrated by its relationship to altered ADC and FA values, there is no relationship to short-term neurodevelopment outcome unless there are invisible posterior crossroads, representing a severe form of global high T2 signal intensity.
EEG abnormalities within the first month of life significantly predict adverse neurodevelopment at a corrected age of 12 to 18 months in the current preterm survivor.
Absent cyclicity on aEEG within 24 h of age was associated with poor outcome in preterm infants.
EEG findings in PVL differed according to the severity of PVL and the time of recording. To detect PVL, > or =2 EEG recordings are recommended, 1 within 48 hours after birth, to detect ASAs, and 1 in the second week of life, to detect CSAs.
A robot working among pedestrians can attract crowds of people around it, and consequentially become a bothersome entity causing congestion in narrow spaces. To address this problem, our idea is to endow the robot with capability to understand humans' crowding phenomena. The proposed mechanism consists of three underlying models: a model of pedestrian flow, a model of pedestrian interaction, and a model of walking comfort. Combining these models a robot is able to simulate hypothetical situation
A robot working among pedestrians can attract crowds of people around it, and consequentially become a bothersome entity causing congestion in narrow spaces. To address this problem, our idea is to endow the robot with capability to understand humans' crowding phenomena. The proposed mechanism consists of three underlying models: a model of pedestrian flow, a model of pedestrian interaction, and a model of walking comfort. Combining these models a robot is able to simulate hypothetical situation
Social robots working among pedestrians can attract crowds of people around them and consequently become bothersome entities causing congestion in narrow spaces. This in turn can affect the comfort of pedestrians who wish to pass through. To address this problem, our idea is to endow the robot with three capabilities: anticipating pedestrian crowding around the robot, understanding pedestrians' walking comfort, and planning to avoid congestions in advance. Combining several elementary pedestrian
Our results indicated that abnormal brushes on refiltered EEGs were strongly associated with white matter injury.
The DWI findings provided additional information regarding PVL. Among the findings, the association of the presence of decreased diffusivity in the corticospinal tract with later motor impairment was the most interesting.
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